{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "03. Computer vision & convolutional neural networks in TensorFlow Exercise Solution.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/ashikshafi08/Learning_Tensorflow/blob/main/Exercise%20Solutions/%F0%9F%9B%A0%20%2003_Computer_vision_%26_convolutional_neural_networks_in_TensorFlow_Exercise_Solution.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Wuvker0kaUaf"
      },
      "source": [
        "# 03. Computer vision & convolutional neural networks in TensorFlow Exercise Solution\n",
        "\n",
        "### Questionnaire\n",
        "1. Spend 20-minutes reading and interacting with the [CNN explainer website](https://poloclub.github.io/cnn-explainer/).\n",
        "  - What are the key terms? e.g. explain convolution in your own words, pooling in your own words\n",
        "\n",
        "2. Play around with the \"understanding hyperparameters\" section in the [CNN explainer](https://poloclub.github.io/cnn-explainer/) website for 10-minutes.\n",
        "  - What is the kernel size?\n",
        "  - What is the stride?\n",
        "  - How could you adjust each of these in TensorFlow code?\n",
        "\n",
        "3. Take 10 photos of two different things and build your own CNN image classifier using the techniques we've built here.\n",
        "\n",
        "4. Find an ideal learning rate for a simple convolutional neural network model on your the 10 class dataset."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "IMC92s38uvXQ"
      },
      "source": [
        "# Importing the needed packages \n",
        "import tensorflow as tf\n",
        "import pandas as pd \n",
        "import numpy as np \n",
        "import matplotlib.pyplot as plt"
      ],
      "execution_count": 26,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "5TJRZMbFcm1V"
      },
      "source": [
        "1. Spend 20-minutes reading and interacting with the [CNN explainer website](https://poloclub.github.io/cnn-explainer/).\n",
        "\n",
        "What are the key terms? e.g. explain convolution in your own words, pooling in your own words\n",
        "- A **CNN** is a neural network algorithm used to recognize patters in data\n",
        " "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "yAxXuoHvqNJi"
      },
      "source": [
        "### 3. Take 10 photos of two different things and build your own CNN image classifier using the techniques we've built here.\n",
        "\n",
        "I have my own image classifier dataset in my drive. This dataset contains 10 images of hot dog and another 10 images of random things (not a hot dog). \n",
        "\n",
        "The goal is to train a classifier that will classify between hot dog and not dog. \n",
        "\n",
        "Likewise feel free to use your own dataset. "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "h1QqYdgPosNG",
        "outputId": "c6870ef0-8f39-4901-9634-f89e24f05c44"
      },
      "source": [
        "from google.colab import drive \n",
        "drive.mount('/content/drive')"
      ],
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ugWsaSw5ovBs"
      },
      "source": [
        "# Getting the data path \n",
        "data_dir = 'drive/MyDrive/CNN_dataset'\n",
        "hot_dog_path = 'drive/MyDrive/CNN_dataset/hot_dog'\n",
        "not_hot_dog_path = 'drive/MyDrive/CNN_dataset/not_hot_dog'"
      ],
      "execution_count": 28,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "PLxen_1hq7WW",
        "outputId": "90254645-539f-4274-915e-7d5eb8f296ba"
      },
      "source": [
        "# Using ImageDataGenerators to read in images with labels \n",
        "from tensorflow.keras.preprocessing.image import ImageDataGenerator\n",
        "\n",
        "# Creating a instance of the ImageDataGenerator \n",
        "train_datagen = ImageDataGenerator(rescale = 1/255., \n",
        "                                   validation_split = 0.3) # creating a valid split in the train data\n",
        "\n",
        "# Grabbing our image file from directories \n",
        "train_data = train_datagen.flow_from_directory(data_dir , \n",
        "                                               batch_size = 2 , \n",
        "                                               target_size = (200 , 200), \n",
        "                                               class_mode = 'binary', \n",
        "                                               seed = 42 , \n",
        "                                               subset = 'training')\n",
        "\n",
        "valid_data = train_datagen.flow_from_directory(data_dir , \n",
        "                                               batch_size = 2 , \n",
        "                                               target_size = (200 , 200) , \n",
        "                                               class_mode = 'binary' , \n",
        "                                               seed = 42 , \n",
        "                                               subset = 'validation')"
      ],
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Found 14 images belonging to 2 classes.\n",
            "Found 5 images belonging to 2 classes.\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 511
        },
        "id": "97hUSqbir2kj",
        "outputId": "ab11acca-f48e-4c76-fb62-66852ba06145"
      },
      "source": [
        "# Let's do a simple visualization (checking purpose)\n",
        "x , y  = train_data.next()\n",
        "for i in range(2):\n",
        "  image = x[i]\n",
        "  label = y[i]\n",
        "  plt.axis(False)\n",
        "  # print(label) --> for checking whether it's plotting right ones\n",
        "  if label == 1.0:\n",
        "    label = 'not_hot_dog'\n",
        "  else:\n",
        "    label = 'hot_dog'\n",
        "  plt.title(label)\n",
        "  plt.imshow(image)\n",
        "  plt.show()"
      ],
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "N7a2OeFbwbJ0",
        "outputId": "9dabe856-1df1-4c10-c078-1dd052efcb4d"
      },
      "source": [
        "x.shape"
      ],
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(2, 200, 200, 3)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 31
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "66AcyGccukIZ",
        "outputId": "fe603b3e-a001-4b5c-f779-4135d411a685"
      },
      "source": [
        "# Building a simple model \n",
        "from tensorflow.keras import layers \n",
        "\n",
        "model = tf.keras.Sequential([\n",
        "  layers.Conv2D(filters = 2 , kernel_size = 1 , \n",
        "                activation = 'relu' , \n",
        "                input_shape = (200 , 200, 3)),\n",
        "\n",
        "  layers.MaxPool2D(pool_size= 1 , \n",
        "                   padding = 'valid'), \n",
        "   layers.Conv2D(filters = 2 , kernel_size = 1 , \n",
        "                activation = 'relu' ),\n",
        "  layers.MaxPool2D(1 , padding= 'valid'),\n",
        "  layers.Flatten(),\n",
        "  layers.Dense(1 , activation= 'sigmoid')\n",
        "\n",
        "])\n",
        "\n",
        "model.summary()"
      ],
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Model: \"sequential_9\"\n",
            "_________________________________________________________________\n",
            "Layer (type)                 Output Shape              Param #   \n",
            "=================================================================\n",
            "conv2d_18 (Conv2D)           (None, 200, 200, 2)       8         \n",
            "_________________________________________________________________\n",
            "max_pooling2d_18 (MaxPooling (None, 200, 200, 2)       0         \n",
            "_________________________________________________________________\n",
            "conv2d_19 (Conv2D)           (None, 200, 200, 2)       6         \n",
            "_________________________________________________________________\n",
            "max_pooling2d_19 (MaxPooling (None, 200, 200, 2)       0         \n",
            "_________________________________________________________________\n",
            "flatten_9 (Flatten)          (None, 80000)             0         \n",
            "_________________________________________________________________\n",
            "dense_9 (Dense)              (None, 1)                 80001     \n",
            "=================================================================\n",
            "Total params: 80,015\n",
            "Trainable params: 80,015\n",
            "Non-trainable params: 0\n",
            "_________________________________________________________________\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "iYge0YRcv52z",
        "outputId": "edea5129-f269-4c5d-b732-a9daa784aa6f"
      },
      "source": [
        "# Compiling the model\n",
        "model.compile(loss = tf.keras.losses.BinaryCrossentropy() , \n",
        "              optimizer = tf.keras.optimizers.Adam() , \n",
        "              metrics = ['accuracy'])\n",
        "\n",
        "# Fit the model \n",
        "history = model.fit(train_data , \n",
        "                    epochs = 20 , \n",
        "                    validation_data = valid_data )"
      ],
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Epoch 1/20\n",
            "7/7 [==============================] - 6s 896ms/step - loss: 0.9484 - accuracy: 0.4286 - val_loss: 0.7271 - val_accuracy: 0.6000\n",
            "Epoch 2/20\n",
            "7/7 [==============================] - 5s 728ms/step - loss: 0.4720 - accuracy: 0.7857 - val_loss: 0.7373 - val_accuracy: 0.4000\n",
            "Epoch 3/20\n",
            "7/7 [==============================] - 5s 716ms/step - loss: 0.3734 - accuracy: 0.7857 - val_loss: 0.8230 - val_accuracy: 0.4000\n",
            "Epoch 4/20\n",
            "7/7 [==============================] - 5s 762ms/step - loss: 0.2723 - accuracy: 0.8571 - val_loss: 0.8955 - val_accuracy: 0.8000\n",
            "Epoch 5/20\n",
            "7/7 [==============================] - 5s 718ms/step - loss: 0.1943 - accuracy: 1.0000 - val_loss: 0.9630 - val_accuracy: 0.8000\n",
            "Epoch 6/20\n",
            "7/7 [==============================] - 5s 698ms/step - loss: 0.1383 - accuracy: 1.0000 - val_loss: 1.0994 - val_accuracy: 0.6000\n",
            "Epoch 7/20\n",
            "7/7 [==============================] - 5s 746ms/step - loss: 0.0761 - accuracy: 1.0000 - val_loss: 1.1139 - val_accuracy: 0.2000\n",
            "Epoch 8/20\n",
            "7/7 [==============================] - 5s 750ms/step - loss: 0.0626 - accuracy: 1.0000 - val_loss: 1.1782 - val_accuracy: 0.4000\n",
            "Epoch 9/20\n",
            "7/7 [==============================] - 5s 779ms/step - loss: 0.0473 - accuracy: 1.0000 - val_loss: 1.5566 - val_accuracy: 0.6000\n",
            "Epoch 10/20\n",
            "7/7 [==============================] - 5s 731ms/step - loss: 0.0322 - accuracy: 1.0000 - val_loss: 1.3828 - val_accuracy: 0.6000\n",
            "Epoch 11/20\n",
            "7/7 [==============================] - 5s 748ms/step - loss: 0.0215 - accuracy: 1.0000 - val_loss: 1.3740 - val_accuracy: 0.4000\n",
            "Epoch 12/20\n",
            "7/7 [==============================] - 5s 663ms/step - loss: 0.0182 - accuracy: 1.0000 - val_loss: 1.4166 - val_accuracy: 0.8000\n",
            "Epoch 13/20\n",
            "7/7 [==============================] - 6s 863ms/step - loss: 0.0132 - accuracy: 1.0000 - val_loss: 1.4874 - val_accuracy: 0.6000\n",
            "Epoch 14/20\n",
            "7/7 [==============================] - 5s 776ms/step - loss: 0.0112 - accuracy: 1.0000 - val_loss: 1.5555 - val_accuracy: 0.6000\n",
            "Epoch 15/20\n",
            "7/7 [==============================] - 8s 1s/step - loss: 0.0098 - accuracy: 1.0000 - val_loss: 1.5654 - val_accuracy: 0.6000\n",
            "Epoch 16/20\n",
            "7/7 [==============================] - 7s 1s/step - loss: 0.0087 - accuracy: 1.0000 - val_loss: 1.5468 - val_accuracy: 0.8000\n",
            "Epoch 17/20\n",
            "7/7 [==============================] - 5s 575ms/step - loss: 0.0077 - accuracy: 1.0000 - val_loss: 1.5632 - val_accuracy: 0.8000\n",
            "Epoch 18/20\n",
            "7/7 [==============================] - 5s 687ms/step - loss: 0.0071 - accuracy: 1.0000 - val_loss: 1.5735 - val_accuracy: 0.8000\n",
            "Epoch 19/20\n",
            "7/7 [==============================] - 5s 744ms/step - loss: 0.0062 - accuracy: 1.0000 - val_loss: 1.6150 - val_accuracy: 0.6000\n",
            "Epoch 20/20\n",
            "7/7 [==============================] - 5s 675ms/step - loss: 0.0058 - accuracy: 1.0000 - val_loss: 1.6679 - val_accuracy: 0.6000\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "tLCaX7kwxZDf"
      },
      "source": [
        "### 4. Find an ideal learning rate for a simple convolutional neural network model on your the 10 class dataset."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jALMjd455it7"
      },
      "source": [
        "# Lets import learning rate scheduler \n",
        "lr_scheduler = tf.keras.callbacks.LearningRateScheduler(lambda epoch: 1e-4 * 10**(epoch/20))"
      ],
      "execution_count": 34,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "G5lsypd85u2N",
        "outputId": "ecfefc55-2318-4b20-f329-022e1edeb0e1",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "# Again fitting the same model but with our lr scheduler \n",
        "\n",
        "from tensorflow.keras import layers \n",
        "\n",
        "lr_model = tf.keras.Sequential([\n",
        "  layers.Conv2D(filters = 2 , kernel_size = 1 , \n",
        "                activation = 'relu' , \n",
        "                input_shape = (200 , 200, 3)),\n",
        "\n",
        "  layers.MaxPool2D(pool_size= 1 , \n",
        "                   padding = 'valid'), \n",
        "   layers.Conv2D(filters = 2 , kernel_size = 1 , \n",
        "                activation = 'relu' ),\n",
        "  layers.MaxPool2D(1 , padding= 'valid'),\n",
        "  layers.Flatten(),\n",
        "  layers.Dense(1 , activation= 'sigmoid')\n",
        "\n",
        "])\n",
        "\n",
        "# Compiling the model\n",
        "lr_model.compile(loss = tf.keras.losses.BinaryCrossentropy() , \n",
        "              optimizer = tf.keras.optimizers.Adam() , \n",
        "              metrics = ['accuracy'])\n",
        "\n",
        "# Fit the model \n",
        "lr_history = lr_model.fit(train_data , \n",
        "                    epochs = 10 , \n",
        "                    validation_data = valid_data  , \n",
        "                    callbacks = [lr_scheduler])"
      ],
      "execution_count": 35,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Epoch 1/10\n",
            "7/7 [==============================] - 6s 912ms/step - loss: 0.7244 - accuracy: 0.4286 - val_loss: 0.6495 - val_accuracy: 0.6000\n",
            "Epoch 2/10\n",
            "7/7 [==============================] - 5s 677ms/step - loss: 0.6941 - accuracy: 0.7857 - val_loss: 0.7198 - val_accuracy: 0.4000\n",
            "Epoch 3/10\n",
            "7/7 [==============================] - 5s 630ms/step - loss: 0.6509 - accuracy: 0.9286 - val_loss: 0.7933 - val_accuracy: 0.4000\n",
            "Epoch 4/10\n",
            "7/7 [==============================] - 5s 627ms/step - loss: 0.6410 - accuracy: 0.8571 - val_loss: 0.8674 - val_accuracy: 0.4000\n",
            "Epoch 5/10\n",
            "7/7 [==============================] - 4s 695ms/step - loss: 0.6348 - accuracy: 0.7857 - val_loss: 0.9372 - val_accuracy: 0.4000\n",
            "Epoch 6/10\n",
            "7/7 [==============================] - 5s 677ms/step - loss: 0.6258 - accuracy: 0.8571 - val_loss: 0.9214 - val_accuracy: 0.4000\n",
            "Epoch 7/10\n",
            "7/7 [==============================] - 5s 739ms/step - loss: 0.6144 - accuracy: 0.8571 - val_loss: 0.8943 - val_accuracy: 0.4000\n",
            "Epoch 8/10\n",
            "7/7 [==============================] - 5s 702ms/step - loss: 0.5999 - accuracy: 1.0000 - val_loss: 0.8374 - val_accuracy: 0.4000\n",
            "Epoch 9/10\n",
            "7/7 [==============================] - 5s 662ms/step - loss: 0.5833 - accuracy: 0.7857 - val_loss: 0.7487 - val_accuracy: 0.4000\n",
            "Epoch 10/10\n",
            "7/7 [==============================] - 5s 631ms/step - loss: 0.5641 - accuracy: 0.7857 - val_loss: 0.6413 - val_accuracy: 0.4000\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "XhFd3Nm96I3f",
        "outputId": "1e925aab-143a-45b9-f70f-4ccb121196e4",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 462
        }
      },
      "source": [
        "# Plot the learning rate versus the loss (to figure out where is the inflection point)\n",
        "lrs = 1e-4 * (10 ** (np.arange(10)/20))\n",
        "plt.figure(figsize=(10, 7))\n",
        "plt.semilogx(lrs, lr_history.history[\"loss\"]) # we want the x-axis (learning rate) to be log scale\n",
        "plt.xlabel(\"Learning Rate\")\n",
        "plt.ylabel(\"Loss\")\n",
        "plt.title(\"Learning rate vs. loss\");"
      ],
      "execution_count": 41,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x504 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vxFcL-I36TN0",
        "outputId": "ea978661-0e26-4fe4-fe2a-2d21719c67e7",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "# Our learning rate from the graph above \n",
        "lr = 2 * 1e-4\n",
        "lr"
      ],
      "execution_count": 47,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.0002"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 47
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ubpK2Gv26xX5",
        "outputId": "b01cffd6-5b7e-4d65-dcca-88defe256e94",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "# Again fitting the same model but with our lr scheduler \n",
        "\n",
        "from tensorflow.keras import layers \n",
        "\n",
        "lr_model = tf.keras.Sequential([\n",
        "  layers.Conv2D(filters = 2 , kernel_size = 1 , \n",
        "                activation = 'relu' , \n",
        "                input_shape = (200 , 200, 3)),\n",
        "\n",
        "  layers.MaxPool2D(pool_size= 1 , \n",
        "                   padding = 'valid'), \n",
        "   layers.Conv2D(filters = 2 , kernel_size = 1 , \n",
        "                activation = 'relu' ),\n",
        "  layers.MaxPool2D(1 , padding= 'valid'),\n",
        "  layers.Flatten(),\n",
        "  layers.Dense(1 , activation= 'sigmoid')\n",
        "\n",
        "])\n",
        "\n",
        "# Compiling the model\n",
        "lr_model.compile(loss = tf.keras.losses.BinaryCrossentropy() , \n",
        "              optimizer = tf.keras.optimizers.Adam(learning_rate = lr) , \n",
        "              metrics = ['accuracy'])\n",
        "\n",
        "# Fit the model \n",
        "lr_history = lr_model.fit(train_data , \n",
        "                    epochs = 10 , \n",
        "                    validation_data = valid_data)"
      ],
      "execution_count": 45,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Epoch 1/10\n",
            "7/7 [==============================] - 10s 1s/step - loss: 0.6910 - accuracy: 0.3571 - val_loss: 0.6953 - val_accuracy: 0.6000\n",
            "Epoch 2/10\n",
            "7/7 [==============================] - 5s 738ms/step - loss: 0.6788 - accuracy: 0.6429 - val_loss: 0.6947 - val_accuracy: 0.6000\n",
            "Epoch 3/10\n",
            "7/7 [==============================] - 5s 628ms/step - loss: 0.6588 - accuracy: 0.7143 - val_loss: 0.6833 - val_accuracy: 0.8000\n",
            "Epoch 4/10\n",
            "7/7 [==============================] - 5s 631ms/step - loss: 0.6483 - accuracy: 0.6429 - val_loss: 0.6672 - val_accuracy: 0.8000\n",
            "Epoch 5/10\n",
            "7/7 [==============================] - 5s 700ms/step - loss: 0.6304 - accuracy: 0.7857 - val_loss: 0.6423 - val_accuracy: 0.6000\n",
            "Epoch 6/10\n",
            "7/7 [==============================] - 4s 669ms/step - loss: 0.6128 - accuracy: 0.8571 - val_loss: 0.6248 - val_accuracy: 0.8000\n",
            "Epoch 7/10\n",
            "7/7 [==============================] - 5s 736ms/step - loss: 0.6001 - accuracy: 0.7857 - val_loss: 0.6113 - val_accuracy: 0.8000\n",
            "Epoch 8/10\n",
            "7/7 [==============================] - 5s 689ms/step - loss: 0.5839 - accuracy: 0.7857 - val_loss: 0.5913 - val_accuracy: 0.8000\n",
            "Epoch 9/10\n",
            "7/7 [==============================] - 5s 698ms/step - loss: 0.5697 - accuracy: 0.7857 - val_loss: 0.5735 - val_accuracy: 0.8000\n",
            "Epoch 10/10\n",
            "7/7 [==============================] - 5s 748ms/step - loss: 0.5523 - accuracy: 0.7857 - val_loss: 0.5590 - val_accuracy: 0.8000\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "NjycSEUOcIPF"
      },
      "source": [
        "Wow! We cann see that our model has improved a bit. Tweaking the learning rate is really important. And remember we trained our model with only few samples (10 pics) try training your model with more data and the results will be better than this. "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HAQ1-P5bcvdj"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}